Generally no company is ever short of data today; the digital connected world that we live in ensures this with data from machines, men, social media, and ERPs always in play. However, how many companies actually understand, access and utilize this data as it can and should be, is questionable. This is the crux of people or HR analytics, and the difference between HR being a mere pawn in the business game, versus being a strategic partner at the CXO table.

Talent analytics is the key to unlock the true value of talent. Unfortunately, most companies are getting it wrong more often than right. According to Helen Friedman, global leader of human capital analytics at Willis Towers Watson, the factors that go into successful data analytics are a scaled data approach, clear ownership, and fundamentally strong analytics and data capabilities. Keeping it simple in the initial stages is critical to talent analytics success. Here are some of the companies that seem to have cracked the talent analytics code and are reaping rewards.

Electronic Arts Inc.: A global provider of interactive entertainment software, EA made data analytics come to life with the unrelenting leadership focus and right decisions. Its old HRIS was outdated, doling out transactional services to customers. This tech-savvy maker of games such as The Sims and EA SPORTS FIFA wished to bring tech-savviness closer back home, to manage its quirky and innovative people better. The team started off by delivering hard-coded, monthly workforce reports to HR and business leaders, giving them the much needed workforce visibility. With new and reliable knowledge about hiring, movements, terminations, demographic shifts etc., the business was empowered. The next stage was to automate this, and for this, Workday's new HR management system along with Visier, a cloud-based analytics tool (SaaS) was chosen. EA and Visier collaborated to save 24 weeks of labor per year, delivering high value. Apart from this, EA also built “sensitivity analysis“ trend reports for headcount management by tying it into hiring and termination trends. Thus, EA brought on a better way to hire, retain and engage its people advantage.

BAE Systems Inc.: The company’s HR analytics effort started out small, and today is managed by a dedicated workforce-intelligence team. Carol Darling, vice president of workforce analytics and HR compliance, talent acquisition ops and global workforce planning, stated that their approach to talent analytics was to continuously track employee data in critical roles. This gives a comprehensive view of hiring, attrition, retention and demographics data, enabling business leaders to take data-backed talent decisions based on employees’ strengths and weaknesses. Such talent intelligence is delivered in customized “talent dashboards”a A case in point being the generational-diversity analysis that HR presents to business. Not only does it cover the current mix, it predicts future changes and thereby helps recommend diversity-friendly people interventions to help manage business smoothly. The journey for BAE started with compliance data—a clean data set which could provide great insights. From a simple dashboard, BAE moved to a combination of Alteryx, a self-service analytics platform, and Tableaux, a visual analytics platform. From segmentation of skills as per talent pipelines to creating heat-maps for flight-risks, BAE is creating great talent analytics experiences for business.

IBM: Big Blue is a leader in predictive social analytics. This people-focus kicked off with an initial project that focussed on analyzing social media to get a real-time understanding of employee engagement. Gradually, the team found that 48% of the variability in employee-engagement scores could be found out beforehand, by analyzing social-media-data use among employees. This spurred the creation of Social Pulse, a "social-media sentiment" tool and created a data-based channel to hear the voice of the employee. For example, employees posted their dissent about the reimbursement policy for ride-sharing services like Uber on the company social media platform, Connections. Within 24 hours, 100 "likes" and 50 comments ensued; the CHRO was alerted by the analytics team, and the policy was changed after some deliberation. A true success story that changed the lives of IBM employees for the better.

While these are just three of the many HR analytics evangelists and adopters, it begs the question: What is the recipe for people analytics success? Some experts espouse visionary leadership, disruptive thinking, clear business alignment, comfort with exploration / failure, and collaboration. A two-pronged careful approach works well, according to Matt Stevenson, partner with Mercer's Workforce Strategy and Analytics group. One must start small at the outset and prioritize the basics such as effective and efficient data collection and reporting. This in itself requires immense capabilities in data science, talent insights etc. The next step is to make the data actionable i.e. predicting outcomes through data modelling.

The jump from the first to the second stage is a huge one, and often where many companies falter. Organizations must build an inherent data-readiness and tackle real-world dynamic challenges. For example, while it is good to make statements such as “People leave employers because of bad managers,” one needs data to prove it and design and deploy the correct interventions. One must thus move from mere data exploration to a more advanced “data inquiry”, and invest in the right technologies and people to make this shift.